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Unknown - 3.7 MB -
MD5: 7b2f980ed53e897325b368ae7d142d27
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Unknown - 5.2 MB -
MD5: 549a623d10678fc1a10f16934e9e0076
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Dec 16, 2015 -
Genealogical information for maize pre-breeding materials in the Seeds of Discovery-MasAgro Biodiversidad project: 2013-2015
Unknown - 107.7 KB -
MD5: c1e83723c73defd7335485ee35990641
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Dec 16, 2015 -
Genealogical information for maize pre-breeding materials in the Seeds of Discovery-MasAgro Biodiversidad project: 2013-2015
Unknown - 768 B -
MD5: ab91571afa2841b458f37c4bc28aaba1
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Dec 16, 2015 -
Genealogical information for maize pre-breeding materials in the Seeds of Discovery-MasAgro Biodiversidad project: 2013-2015
Unknown - 302.2 KB -
MD5: 07f324d88e9d531754dbf0ab6d0b6cae
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Dec 16, 2015 -
Genealogical information for maize pre-breeding materials in the Seeds of Discovery-MasAgro Biodiversidad project: 2013-2015
Unknown - 73.0 KB -
MD5: ff9f5d98e4020ad7bbe76ca66c7bff30
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JPEG Image - 442.7 KB -
MD5: 3a2aa708bc78d4fc3a8037bebdb9e65c
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Adobe PDF - 915.0 KB -
MD5: cff6e250d0a709b99d392868684a049e
Announcement describing new CML lines released in 2015. |
Dec 14, 2015 - CIMMYT Research Data
González-Camacho, Juan Manuel; Crossa, Jose; Pérez-Rodríguez, Paulino; Ornella, Leonardo; Gianola, Daniel, 2015, "Genome-enabled prediction using probabilistic neural network classifiers", https://hdl.handle.net/11529/10576, CIMMYT Research Data & Software Repository Network, V1
Non-parametric methods have been shown to be effective in genome-enabled prediction, in particular, the multi-layer perceptron (MLP) and the radial basis function neural network (RBFNN). In this study, we evaluated and compared the performance of MLP classifier versus the probabi... |
Unknown - 59.2 MB -
MD5: 6f3556758db2bb5870426120d28f43a1
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